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How to build a successful human-robot rescue team

Though fiction often paints them as a threat to our safety, robots are increasingly helping to save our lives. From tiny, cockroach-inspired automatons designed to search in rubble for signs of life, to the DARPA Robotics Challenge, robots are really getting their bionic hands dirty.

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Now a new communications system, designed by MIT, could be a critical tool for helping humans and robots work together in emergency situations.

According to the researchers, robots tend to overwhelm their human colleagues with too much information. Autonomous robots often send each other vast swathes of data during service, including location, movements and more, but for humans much of it is superfluous. So a team at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) have designed a new system of collaboration, which they say "reduces the need for communication by 60 percent".

It's somewhat necessary for robots to share the level of detail that they do -- robots are less able to respond to contextual changes without prior information. This means they have to share, and constantly update, a model of their environment. This model is always adjusting itself and working out probabilities of how a situation might develop -- which is vital if information does change, but is time-consuming if it doesn't.

The new model reduces this need. Known as a "decentralised partially observable Markov decision process", or the catchier Dec-POMDP for short, the system allows probability to be factored in, but also calculates how successful a potential action may be. So rather than broadcasting all of its internal machinations, the robot will instead perform "a cost benefit analysis based on its model of the world, its expectations of its fellows' actions and the likelihood of accomplishing the joint goal efficiently".

This could, says Julie Shah, who co-authored the research, "be the difference between a team that can function effectively versus a team that just plain can't".

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The new system may not just be useful for humans, either -- it could also reduce power consumption on robots.

The system hasn't yet been implemented in real life teams yet, but researchers describe the innovation as "very exciting" and are working on concepts for future trials.